Triple
T2860414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jetstar Airways |
E63305
|
entity |
| Predicate | callsign |
P1565
|
FINISHED |
| Object | JETSTAR |
E63305
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: JETSTAR | Statement: [Jetstar Airways, callsign, JETSTAR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JETSTAR Context triple: [Jetstar Airways, callsign, JETSTAR]
-
A.
Jetstar Airways
chosen
Jetstar Airways is an Australian low-cost airline operating domestic and international flights, owned by the Qantas Group.
-
B.
Jetstar Japan
Jetstar Japan is a Japanese low-cost airline operating domestic and international flights, partly owned by Qantas and Japan Airlines.
-
C.
Virgin Australia
Virgin Australia is a major Australian airline offering domestic and international passenger services with a focus on full-service amenities and extensive route networks.
-
D.
Thai AirAsia
Thai AirAsia is a Thai low-cost airline operating domestic and international flights, and is part of the wider AirAsia group based in Southeast Asia.
-
E.
KrisFlyer
KrisFlyer is the loyalty program of Singapore Airlines, allowing members to earn and redeem miles for flights, upgrades, and other travel-related rewards across the airline and its partners.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf8c676c8190ab29f89d50bd09c3 |
completed | March 7, 2026, 8:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b055e0c8088190a0fa67c9c14fc29b |
completed | March 10, 2026, 5:33 p.m. |
Created at: March 6, 2026, 10:02 p.m.